docstr: Creates a new untrained component (see parent class for full docstring).
docstr_tok: ["Creates","a","new","untrained","component","(","see","parent","class","for","full","docstring",")","."]
code: def create(
      cls,
      config: Dict[Text, Any],
      model_storage: ModelStorage,
      resource: Resource,
      execution_context: ExecutionContext,
  ) -> GraphComponent:
      """Creates a new untrained component (see parent class for full docstring)."""
      return cls(
          config, execution_context.node_name, model_storage, resource
      )
  
imports: import logging
  from typing import Any, Text, Dict, List, Type
  from sklearn.feature_extraction.text import TfidfVectorizer
  from rasa.engine.recipes.default_recipe import DefaultV1Recipe
  from rasa.engine.graph import ExecutionContext, GraphComponent
  from rasa.engine.storage.resource import Resource
  from rasa.engine.storage.storage import ModelStorage
  from rasa.nlu.featurizers.sparse_featurizer.sparse_featurizer import SparseFeaturizer
  from rasa.nlu.tokenizers.tokenizer import Tokenizer
  from rasa.shared.nlu.training_data.training_data import TrainingData
  from rasa.shared.nlu.training_data.features import Features
  from rasa.shared.nlu.training_data.message import Message
  from rasa.nlu.constants import DENSE_FEATURIZABLE_ATTRIBUTES, FEATURIZER_CLASS_ALIAS
  from joblib import dump, load
  from rasa.shared.nlu.constants import TEXT, TEXT_TOKENS, FEATURE_TYPE_SENTENCE, FEATURE_TYPE_SEQUENCE
label_desc: Use image node_id 6 for calling the TfIdfFeaturizer obj's underlying member method code with example usage: obj.create(cls, config, model_storage, resource, execution_context) and returns: cls